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Questions tagged [optuna]

Optuna is Hyper-parameter Optimization Framework for Python (versions 2.7 and 3.*) that helps to find the best parameters for Machine Learning models via checking various combinations of parameters' values. Site: https://optuna.org

Optuna is Hyper-parameter Optimization Framework for Python (versions 2.7 and 3.*) that helps to find the best parameters for Machine Learning models via checking various combinations of parameters' values.

Resources:

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Hyperparameter optimization in pytorch (currently with sklearn GridSearchCV)

I use this(link) pytorch tutorial and wish to add the grid search functionality in it ,sklearn.model_selection.GridSearchCV (link), in order to optimize the hyper parameters. I struggle in understanding what X and Y in gs.fit(x,y) should be; per the…
Henrik
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'monotone_constraints ' shows warning of not being used in PythonAPI of XGB

On trying monotone_constraint parameter for xgb , some of the trials shows warning for below code snippet def objective(trial): param = {"objective": "reg:squarederror", "monotone_constraints":constraint, "booster":…
RASHMITHA KAMATH
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Getting a TypeError when trying to save Optuna.Study in an optimize callback

I'm running some Optuna study, and when I try to save it with joblib.dump, I'm getting the following: TypeError: cannot pickle '_io.TextIOWrapper' object I also try to pickle.dump(study, open('name.pkl', 'wb')), but I'm getting the same in both…
Alex Finkelshtein
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Getting SIGKILL when running study optimization with Optuna on PyCharm

I am trying to run a study, using the optimize function with the default sampler and Median pruner. every run crashes, sometimes after 1 succefull trial sometimes without completing any. The crash message is: Process finished with exit code 137…
Alex Finkelshtein
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strange behavior of roc_auc_score, 'roc_auc', 'auc'

While optimizing parameters for xgboost I encountered a problem with the roc_auc_score metric. I get significantly different results during cross-validation compared to the results on the training data. class OptunaHyperparamsSearch: def…
Moeu
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Force one specific set of parameters into the sampled batch

I am trying to test different set of parameters in a ML algorithm using Optuna. The automatic sampling of Optuna is very useful, but is there any way to force one specific set of parameters into the proposed batch defined by Optuna? For example if I…
Aurelie Navir
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Can I optimize distributively multiple models at the same time?

I understand that I can do distributed optimization with Optuna. However, I don't know if I can do it with multiple models at the same time? For example: optuna create-study --study-name "distributed-example1" --storage…
Minh Trần Văn
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Tensorflow / keras issue when optimizing with optuna

I'm pretty new to machine learning, I've been trying to teach myself neural networks from following sentdex tutorials. I followed his tutorial on using recurrent neural networks for predicting the price of various crypto-currencies and succeeded…
Alex Kilpatrick
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